Clark State Forest, Indiana (2012)
Clark State Forest, Indiana (2012)
Clark State Forest, Indiana (2012), CHM
Clark State Forest, Indiana (2012)
Clark State Forest, Indiana (2012)
Clark State Forest, Indiana (2012)
Clark State Forest, Indiana (2012), CHM
Clark State Forest, Indiana (2012)

We have the largest archive of data on tree canopy heights within the US.

Canopy Height Model (CHM)

The Canopy Height Model (CHM) dataset is a high-resolution (1 meter) raster layer that maps the tree height as a continuous surface. Each pixel in the CHM represents the tree overstory height above the underlying ground topography. The key data source for creating a CHM is LIDAR data. LIDAR (Light Detection and Ranging) technology enables accurate measurement of elevation for different ground surface types based on the light pulses reflected from the earth. LIDAR systems produce large volumes of 3D point cloud data which can be analyzed to map different surface types and their elevation. The accuracy and quality of a CHM improves with higher point density LIDAR data.


What can you do with Canopy Height Model (CHM) data?

LIDAR canopy derivatives like the CHM dataset helps government agencies, companies and non-profits by supplying accurate and spatially explicit high-resolution tree canopy height data for performing a wide range of mapping and spatial analysis functions. Example applications include:

  • evaluating tree shade for solar energy assessment
  • assessing vegetation risk to power lines and other utility infrastructure
  • modeling of forest metrics like tree size class, basal area, volume etc., in conjunction with suitable field data
  • assessing fuel load and fire risk
  • monitoring logging and forest recovery
  • evaluating the condition of forests in recreational areas
  • improving line of sight radio wave propagation modeling for wireless planning
  • assessing habitat suitability for wildlife
  • creating and analyzing forest inventory
  • assessing accurate visibility in forested regions from ground surface points
  • identifying locations of trees that may qualify for inclusion in a Big Tree Register

Approach

EarthDefine combines LIDAR data with high-resolution imagery data to create the Canopy Height Model (CHM) dataset. A Digital Surface Model (DSM) is created from first returns of the LIDAR point cloud data. An above ground surface model is created by removing bare earth elevations from the DSM. Buildings and tree canopy are differentiated in the above ground surface model using a knowledge based classification system.


Related Products

Tree Canopy

Tree Locations

Land Cover

Impervious Cover

US Building Footprints

Technical Specifications
Resolution1 meter
Height unitsfeet/meter
Minimum Mapping Unit0.005 acre
Accuracy>90%

Contact Us



Phone: 1.800.579.5916
Email: info@earthdefine.com